scholarly journals Demystifying User Data Privacy in the World of IOT

2019 ◽  
Vol 8 (10) ◽  
pp. 4412-4418
Keyword(s):  
Data Privacy ◽  
Security And Privacy ◽  
Privacy Requirements ◽  
Living Things ◽  
The World ◽  
User Data ◽  
Self Test ◽  
User Data Privacy ◽  
Almost All ◽  
Global World

Internet of Things (IoT) would touch upon almost all aspects of everyday life, as a consequence of which, everything (i.e. living and non-living things) will have a counterpart virtual identities on the internet which would be readable, addressable and locatable. Although it would empower its users with 24×7 connectivity around the global world, unknowingly they would also provide it permission to peep into user’s personal world, which can generate a huge risk on the usability of IoT by users. Thus analyzing the framework of IOT from the perspective of user data protection is a very crucial self-test which is required for IoT implementation. Often the term security and privacy are used interchangeably, but in the IoT environment, both these concept would play a crucial but differentiating role. In this paper, we have scanned the IoT environment with the perspective of privacy requirements, possible threats and the mitigating solutions which are currently in use.

Security- and Privacy-Aware Computing in Cloud With User Mobility

2021 ◽  
pp. 879-897
Author(s):  
Sayani Sen ◽  
Sathi Roy ◽  
Suparna Biswas ◽  
Chandreyee Chowdhury
Keyword(s):  
Data Privacy ◽  
Security And Privacy ◽  
Local Processing ◽  
Processing Unit ◽  
Privacy And Security ◽  
Huge Data ◽  
Learning Techniques ◽  
User Data ◽  
User Data Privacy ◽  
Cloud Servers

Today's computational model has been undergoing a huge paradigm shift from personalized, local processing using local processing unit (LPU) to remote processing at cloud servers located globally. Advances in sensor-based smart applications such as smart home, smart health, smart transport, smart environment monitoring, etc. are generating huge data which needs to stored, pre-processed, analyzed using machine learning and deep learning techniques, which are resource-hungry, to generate results to be saved for future reference, and all these need to be done in real time, with scalability support satisfying user data privacy and security that may vary from application to application. In smart application like remote health monitoring and support, patient data needs utmost privacy besides confidentiality, integrity, and availability.

Security- and Privacy-Aware Computing in Cloud With User Mobility

2020 ◽  
pp. 1-20
Author(s):  
Sayani Sen ◽  
Sathi Roy ◽  
Suparna Biswas ◽  
Chandreyee Chowdhury
Keyword(s):  
Data Privacy ◽  
Security And Privacy ◽  
Local Processing ◽  
Processing Unit ◽  
Privacy And Security ◽  
Huge Data ◽  
Learning Techniques ◽  
User Data ◽  
User Data Privacy ◽  
Cloud Servers

Today's computational model has been undergoing a huge paradigm shift from personalized, local processing using local processing unit (LPU) to remote processing at cloud servers located globally. Advances in sensor-based smart applications such as smart home, smart health, smart transport, smart environment monitoring, etc. are generating huge data which needs to stored, pre-processed, analyzed using machine learning and deep learning techniques, which are resource-hungry, to generate results to be saved for future reference, and all these need to be done in real time, with scalability support satisfying user data privacy and security that may vary from application to application. In smart application like remote health monitoring and support, patient data needs utmost privacy besides confidentiality, integrity, and availability.

A Generic Privacy Breach Preventing Methodology for Cloud Based Web Service

2015 ◽  
pp. 426-458 ◽  
Author(s):  
S. R. Murugaiyan ◽  
D. Chandramohan ◽  
T. Vengattaraman ◽  
P. Dhavachelvan
Keyword(s):  
Private Information ◽  
Data Privacy ◽  
Privacy Preserving ◽  
Digital Data ◽  
Cloud Data ◽  
Privacy Breach ◽  
Cloud Data Storage ◽  
User Data ◽  
Information Technology Development ◽  
User Data Privacy

The present focuses on the Cloud storage services are having a critical issue in handling the user's private information and its confidentiality. The User data privacy preserving is a vital facet of online storage in cloud computing. The information in cloud data storage is underneath, staid molests of baffling addict endeavor, and it may leads to user clandestine in a roar privacy breach. Moreover, privacy preservation is an indeed research pasture in contemporary information technology development. Preserving User Data in Cloud Service (PUDCS) happens due to the data privacy breach results to a rhythmic way of intruding high confidential digital storage area and barter those information into business by embezzle others information. This paper focuses on preventing (hush-hush) digital data using the proposed privacy preserving framework. It also describes the prevention of stored data and de-identifying unauthorized user attempts, log monitoring and maintaining it in the cloud for promoting allusion to providers and users.

Designing Secure and Privacy-Aware Information Systems

2017 ◽  
Vol 8 (2) ◽  
pp. 1-25
Author(s):  
Christos Kalloniatis ◽  
Argyri Pattakou ◽  
Evangelia Kavakli ◽  
Stefanos Gritzalis
Keyword(s):  
Information Systems ◽  
Personal Information ◽  
Research Area ◽  
Security And Privacy ◽  
Software Systems ◽  
Economic Relationships ◽  
Analysis And Design ◽  
Privacy Requirements ◽  
Systems Analysis And Design ◽  
User Data

Pervasiveness of information systems is well underway, redefining our social and economic relationships. This technological revolution has generated enormous capabilities, but also enabled the creation of new vulnerabilities and threats. A major challenge in the field of information systems is therefore, to ensure the trustworthiness of the underlying technologies that make possible the generation, collection, storage, processing and transmission of user data at rates more intensive than ever before. Trust in information systems depends on different aspects, one of which is the security of user's data. Data security is referred as the protection of user's data from corruption and unauthorized access. Another important aspect of trust is the protection of user's privacy. Protecting privacy is about complying with user's desires when it comes to handling personal information. Without security to guarantee data protection, appropriate uses of that data cannot be realized. This implies that security and privacy issues are inherently intertwined and should be viewed synergistically. The aim of this paper is to elevate modern practices for ensuring security and privacy during software systems analysis and design. To this end, the basic security and privacy requirements that should be considered are introduced. Additionally, a number of well known methods in the research area of requirements engineering which focus on eliciting and modeling security and privacy requirements are described. Finally, a comparative analysis between these methods is presented.

scholarly journals Traffic model using a novel sniffer that ensures the user data privacy

2019 ◽  
Vol 292 ◽  
pp. 03002
Author(s):  
Albert Espinal ◽  
Rebeca Estrada ◽  
Carlos Monsalve
Keyword(s):  
Traffic Engineering ◽  
Data Privacy ◽  
Traffic Model ◽  
Traffic Classification ◽  
Campus Network ◽  
University Campus ◽  
User Data ◽  
User Data Privacy ◽  
The Impact

Nowadays, the traffic over the networks is changing because of new protocols, devices and applications. Therefore, it is necessary to analyze the impact over services and resources. Traffic Classification of network is a very important prerequisite for tasks such as traffic engineering and provisioning quality of service. In this paper, we analyze the variable packet size of the traffic in an university campus network through the collected data using a novel sniffer that ensures the user data privacy. We separate the collected data by type of traffic, protocols and applications. Finally, we estimate the traffic model that represents this traffic by means of a Poisson process and compute its associated numerical parameters.

Designing Secure and Privacy-Aware Information Systems

2019 ◽  
pp. 390-418
Author(s):  
Christos Kalloniatis ◽  
Argyri Pattakou ◽  
Evangelia Kavakli ◽  
Stefanos Gritzalis
Keyword(s):  
Information Systems ◽  
Personal Information ◽  
Research Area ◽  
Security And Privacy ◽  
Software Systems ◽  
Economic Relationships ◽  
Analysis And Design ◽  
Privacy Requirements ◽  
Systems Analysis And Design ◽  
User Data

Pervasiveness of information systems is well underway, redefining our social and economic relationships. This technological revolution has generated enormous capabilities, but also enabled the creation of new vulnerabilities and threats. A major challenge in the field of information systems is therefore, to ensure the trustworthiness of the underlying technologies that make possible the generation, collection, storage, processing and transmission of user data at rates more intensive than ever before. Trust in information systems depends on different aspects, one of which is the security of user's data. Data security is referred as the protection of user's data from corruption and unauthorized access. Another important aspect of trust is the protection of user's privacy. Protecting privacy is about complying with user's desires when it comes to handling personal information. Without security to guarantee data protection, appropriate uses of that data cannot be realized. This implies that security and privacy issues are inherently intertwined and should be viewed synergistically. The aim of this paper is to elevate modern practices for ensuring security and privacy during software systems analysis and design. To this end, the basic security and privacy requirements that should be considered are introduced. Additionally, a number of well known methods in the research area of requirements engineering which focus on eliciting and modeling security and privacy requirements are described. Finally, a comparative analysis between these methods is presented.

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